Deep Learning for Preoperative Pulmonary Assessment in Thoracic CT

RecruitingOBSERVATIONAL
Enrollment

2,000

Participants

Timeline

Start Date

October 1, 2023

Primary Completion Date

September 30, 2024

Study Completion Date

December 30, 2024

Conditions
Elective Thoracic SurgeryPulmonary FunctionDeep Learning
Interventions
OTHER

Single inspiratory phase computed tomography.

Utilizing deep learning technology in conjunction with single inspiratory phase computed tomography images to accurately predict the pulmonary function indicators of preoperative thoracic surgery patients.

OTHER

Respiratory dual-phase computed tomography.

Utilizing deep learning technology in conjunction with respiratory dual-phase computed tomography images to accurately predict the pulmonary function indicators of preoperative thoracic surgery patients.

Trial Locations (1)

510120

RECRUITING

Department of Cardiothoracic Surgery, the First Affiliated Hospital of Guangzhou Medical College, Guangzhou

Sponsors

Collaborators (1)

All Listed Sponsors
collaborator

GE Healthcare

INDUSTRY

lead

The First Affiliated Hospital of Guangzhou Medical University

OTHER

NCT06477458 - Deep Learning for Preoperative Pulmonary Assessment in Thoracic CT | Biotech Hunter | Biotech Hunter